CI/CD Pipeline in 2026: Stages, Tools and a Working Backend Example

A CI/CD pipeline turns every commit into a repeatable path from source to a running environment: build the artifact, run the checks you trust, then deploy only what passed. In 2026 the tools differ, and the hard part for backends is still the deploy stage, where containers, load balancers, databases, queues and IAM have to stay in sync with the code.

This guide covers the stages of a CI/CD pipeline, how the common tools compare, and a working backend example where infrastructure is declared in application code so the pipeline does not grow a second Terraform project for every service.

What is a CI/CD pipeline?

A CI/CD pipeline is the automation that builds, tests and releases software on every meaningful change. Continuous integration (CI) compiles or packages the code and runs automated checks so broken revisions never sit unnoticed on the main branch. Continuous delivery keeps a release candidate ready to ship; continuous deployment ships it automatically once those checks pass.

For a backend the pipeline usually produces a container image or binary, runs unit and integration tests, then updates a staging or production environment. The deploy stage usually takes the most time, because the application depends on networks, data stores, message queues, secrets and permissions that are not in the same repository as the handler code unless you put them there on purpose.

CI/CD stages at a glance

How the common CI tools compare

None of these products provisions your RDS instance or IAM roles for you: they run jobs, and you supply the commands that build, test and talk to your cloud.

GitHub Actions stores workflows in the repository and can gate production with environment protection rules. GitLab CI/CD does the same inside GitLab with stages and environments. CircleCI focuses on CI speed and caching. Jenkins stays in places that need custom agents, air-gapped networks or long-lived plugin ecosystems. The right pick is usually the one already next to your git host.

Where the deploy stage gets expensive

Build and test stay cheap as long as the app starts with a few commands. Deploy gets expensive when each service needs its own Terraform root module for a load balancer target group, a task definition, a database, a queue, secrets and an IAM role, which is application infrastructure invoked from CI rather than CI itself.

Teams either maintain that infrastructure code separately, adopt a platform that owns the release, or declare the infrastructure next to the handlers so the deploy stage only has to ship the app.

How does Encore fit inside any CI?

Encore is infrastructure from code for TypeScript and Go, with a platform that provisions and deploys into your own AWS or GCP account. GitHub Actions, GitLab CI, CircleCI or Jenkins run your checks, and Encore handles the deploy stage for the databases, queues, object storage, cron jobs and secrets your code declares.

On a git push the platform runs a build and test phase, then provisions infrastructure and deploys. Link the app to GitHub, set each environment's Branch Push to the branch you release from, and connect the cloud account once.

Set up the app

A tiny health endpoint is enough for the pipeline check:

// hello/hello.ts
import { api } from "encore.dev/api";

export const health = api(
  { expose: true, method: "GET", path: "/health" },
  async (): Promise<{ ok: boolean }> => {
    return { ok: true };
  },
);

encore run starts the service locally. An AI coding agent can add another endpoint or a queue in the same change and leave CI to prove the app still starts.

GitHub Actions: check, then let Encore deploy

This workflow installs the CLI, proves the app starts with encore check, and runs tests. Deploy to your own cloud happens through Encore's GitHub integration on the same push to main, not through a second Terraform apply job.

# .github/workflows/ci.yml
name: Backend CI

on:
  push:
    branches: [main]
  pull_request:

jobs:
  verify:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Install Encore CLI
        run: curl -L https://encore.dev/install.sh | bash

      - name: Check the app starts
        run: /home/runner/.encore/bin/encore check 'curl /health'

      - name: Run tests
        run: /home/runner/.encore/bin/encore test

After the app is linked to GitHub and the production environment's Branch Push is set to main, a green push builds, provisions and deploys into the connected AWS or GCP account. Fargate or Cloud Run, the load balancer, and the resources declared in code come from that deploy, and Encore provisions an IAM role for the service. Database sizing and other settings are edited per environment in the dashboard.

If you self-host the runtime instead of using Encore's deploy path, the same CLI fits any CI: authenticate with an auth key from App Settings, then run encore build docker and push the image to your registry, as the TypeScript self-host CI guide shows.

Best fit: TypeScript and Go teams who want CI in GitHub Actions, GitLab CI, CircleCI or Jenkins, and want the deploy stage to provision application infrastructure in their own cloud from the code under test.

Good to know

• Keep secrets out of the repository. Set them with encore secret set --type <env> for each environment type, and inject only non-secret config into self-hosted builds.
• Treat encore check as a start-and-smoke gate. Put deeper assertions in encore test.
• Infrastructure approval can stay manual on production while code deploys automatically, configured per environment.

Related guides

• Continuous deployment tools
• Deploy a Node.js app to AWS
• Deploy a Go API to AWS
• Preview environments
• Terraform alternatives